The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 09, 2023

Filed:

Feb. 20, 2020
Applicant:

Adobe Inc., San Jose, CA (US);

Inventors:

Yikun Xian, Edison, NJ (US);

Tak Yeon Lee, San Jose, CA (US);

Sungchul Kim, San Jose, CA (US);

Ryan Rossi, Mountain View, CA (US);

Handong Zhao, San Jose, CA (US);

Assignee:

Adobe Inc., San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/22 (2019.01); G06F 16/2457 (2019.01); G06F 16/248 (2019.01); G06F 16/901 (2019.01); G06N 3/08 (2023.01); G06N 5/02 (2023.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06F 16/221 (2019.01); G06F 16/248 (2019.01); G06F 16/24578 (2019.01); G06F 16/9024 (2019.01); G06N 5/02 (2013.01);
Abstract

Systems, methods, and non-transitory computer-readable media are disclosed for generating generate explanatory paths for column annotations determined using a knowledge graph and a deep representation learning model. For instance, the disclosed systems can utilize a knowledge graph to generate an explanatory path for a column label determination from a deep representation learning model. For example, the disclosed systems can identify a column and determine a label for the column using a knowledge graph (e.g., a representation of a knowledge graph) that includes encodings of columns, column features, relational edges, and candidate labels. Then, the disclosed systems can determine a set of candidate paths between the column and the determined label for the column within the knowledge graph. Moreover, the disclosed systems can generate an explanatory path by ranking and selecting paths from the set of candidate paths using a greedy ranking and/or diversified ranking approach.


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